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Aditya Nagarajan, a graduate student in our Mechanical and Industrial Engineering Department, won a Second Place Oral Presentation award at the 14th Conference on Artificial and Computational Intelligence and its application to the Environmental Sciences, which was part of the American Meteorological Society's 96th Annual Meeting in New Orleans, Louisiana, in January. Nagarajan’s award-wining presentation was about his research “On Learning Patterns Between GPS Derived Precipitable Water Fields and Radar Reflectivity Fields.” Listen to the Recorded Presentation.

A multi-college collaboration, Nagarajan’s work is being conducted within the Electrical and Computer Engineering (ECE) Department’s Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) under the direction of senior research fellow, Dr. David Pepyne.

Nagarajan’s research is funded by the Jerome M. Paros Fund for Measurement and Environmental Sciences Researchat UMass Amherst, created with a gift of $2 million. Paros is the Founder and CEO of Paroscientific, Inc. and one of the largest contributors to the College of Engineering. Paros received a Distinguished Achievement Award from the university at its commencement ceremonies in 2011. He is an internationally recognized innovator and leader in the field of measurement sciences, the owner of more than 20 U.S. patents, a successful businessman, and a visionary philanthropist.

As recalled by Nagarajan, the research is an outgrowth of a class project he did for ECE Professor Dave McLaughlin’s systems engineering course to understand how it is that a GPS receiver, a barometer, and a thermometer can be used to estimate the amount of water vapor in the atmosphere. That project led to a summer internship with CASA to build two so-called GPS-meteorology stations. These stations – equipped with two of the Digi-Quartz barometers manufactured by Paroscientific, Inc. to allow not only for high-precision water vapor estimates but high-precision, high-sample-rate, barometric-pressure observations – have since been deployed and are being used operationally by National Weather Service (NWS) forecasters in Texas. This internship turned into Nagarajan’s research to explore applications of GPS-meterology, and in particular how it could be used to assist CASA’s mission of severe weather and flood forecasting with its network of X-band weather radars in the Dallas Fort Worth (DFW) metroplex.

According to Nagarajan’s abstract, the amount of water vapor in the atmosphere plays a fundamental role in determining the potential for precipitation, leading to his conjecture that an ability to measure atmospheric water vapor with high temporal and spatial resolution should therefore allow for better precipitation predictions. Nagarajan explained that “The domain of interest in this paper is the DFW Metroplex region, where the Texas Department of Transportation operates some 44 high-quality, dual-frequency GPS continuously operating reference stations). While these stations are not specifically operated for GPS-meteorology, the data they provide is of sufficient quality that we are able to process it – using ASOS (Automated Surface Observing Systems) barometer and thermometer data, the GAMIT (GPS Analysis at MIT) GPS processing software, and standard geospatial interpolation algorithms – to generate, with a 30-minute update rate, the Integrated Precipitable Water (IPW) field as it evolves over the DFW region.”

When the reflectivity fields from Fort Worth’s NWS NEXRAD radar system were superimposed atop the resulting IPW fields, a clear correlation was observed between weather radar reflectivity (precipitation) and IPW. In general, an advecting IPW field (a measure of the total amount of water vapor in the atmosphere which could possibly fall as precipitation) is followed sometime later by an advecting reflectivity field (a measure of precipitation rate).

“Motivated by these observable patterns,” said Nagarajan, “we developed a machine-learning algorithm able to infer from the temporal and spatial correlations between the IPW and radar reflectivity fields a nowcast, or short-term prediction, of what the reflectivity field over the region will be one-hour in the future.”

While the U.S. southwest currently has the most dense networks of GPS stations, continued growth in the number of GPS stations in other regions, both inside and outside the U.S., may soon make it possible to obtain water vapor observations with spatial and temporal resolution sufficient for operational forecasting, using techniques like the one being developed by Nagarajan, over virtually the entire globe.

Nagarajan’s award was the second honor won by UMass College of Engineering students at the AMS meeting. Graduate student Sheila Werth of the ECE department won Best Oral Presentation at the 7th Conference on Weather, Climate, Water, and the New Energy Economy, which was part of the AMS meeting. Her talk was entitled "Evaluating Parameters for Species-Based Classification of Bird Radar Echoes for Wind Energy Site Assessment." Her ECE faculty advisor is Stephen Frasier. See the abstract »